# Clay vs Models.dev

Clay records 1,267,465 monthly visits with -2.7% month-over-month growth and Freemium, Free Trial, Contact for Pricing pricing. Models.dev records 200,451 monthly visits with -3.9% growth and Free pricing.

| Metric | [Clay](https://openaitools.app/tool/clay-2-0) | [Models.dev](https://openaitools.app/tool/models-dev) |
| :--- | :--- | :--- |
| Website URL | https://www.clay.com | https://models.dev |
| Categories | AI Agent, AI Lead Generation, AI Sales, AI CRM | AI Models, AI API, Open Source AI Models, AI Tools Directory |
| Pricing Model | Freemium, Free Trial, Contact for Pricing | Free |
| Monthly Visits | 1,267,465 | 200,451 |
| MoM Growth Rate | -2.7% | -3.9% |
| Primary Market | United States | China |
| Direct Visits | 744,956 | 136,316 |
| Review Score | 4.7 | 4.4 |
| Saved Count | 2 | 0 |
| Supported Platforms | Website | Website |

## Clay

Clay brings together the three pillars of modern go-to-market work: data, reasoning, and activation. On the data side, its marketplace lets you buy and combine records from more than 200 providers under a single contract, with waterfall enrichment that queries multiple sources and keeps the best match. Signals and intent tracking surface job changes, promotions, and buying activity so you know when an account is actually in-market.

On top of that data layer, Clay runs agentic workflows. Its global agent and account agents research companies and people with AI, score and route leads, and write personalized outreach — and you can chain these steps into long-form automations or call them through the CLI and API. Because the same canvas handles enrichment, scoring, and messaging, teams stop stitching together spreadsheets, point tools, and scripts.

The activation layer is what makes the platform practical: sync targeted audiences to LinkedIn, Meta, and Google Ads, push enriched records back into your CRM with reverse ETL, or send personalized sequences through Clay's native sequencer. Clay is aimed at GTM ops, sales, marketing, and enterprise teams that want a repeatable, testable system rather than a pile of one-off campaigns.

**Pricing & Plans:** Clay uses flexible, plan-based pricing with a 14-day free trial and a free entry point for individuals getting started, while larger teams and enterprises are quoted based on seats, credits, and data usage. Contact Clay for detailed enterprise pricing.

- **Waterfall data enrichment:** Query 200+ data and AI providers from one contract and cascade across them to maximize coverage and accuracy.
- **Agentic research & scoring:** Clay's global agent and account agents research companies and people with AI, then score and route leads automatically.
- **Signals & intent tracking:** Monitor job changes, promotions, hiring activity, and other buying signals to target accounts at the right moment.
- **Workflow orchestration & CLI/API:** Chain enrichment, reasoning, and outreach into long-running workflows, or build programmatically with Clay's CLI, API, and MCP tooling.
- **Multi-channel activation:** Sync audiences to LinkedIn, Meta, and Google Ads, push data back to CRM via reverse ETL, and run personalized sequences natively.

**Strengths:** Unifies data enrichment, AI research, and multi-channel activation in a single platform; Marketplace with 200+ providers and waterfall enrichment delivers strong coverage; Powerful workflow automation with CLI, API, and MCP access for technical teams; Large, active community plus Clay University, livestreams, and education resources

**Limitations:** Steep learning curve — the flexible canvas can overwhelm new users; Credit-based data usage costs can scale quickly for high-volume teams; Enterprise pricing is quote-based, which complicates budget planning

[Profile (Markdown)](https://openaitools.app/tool/clay-2-0.md)

## Models.dev

Models.dev exists to answer a very practical developer question: which model should I use, and what will it cost? The site organises every entry under a canonical identifier in the form provider/model, so the same model served by several providers can be compared directly rather than guessed at. Columns cover context window, maximum output, whether input and output are supported, reasoning, tool calling, structured output, temperature control, open versus closed weights, price per million tokens, and release and update dates.

Because model releases move fast, the catalogue is built to stay current, with sortable and searchable tables that let you scan by lab or provider and filter down to what matters. Entries include both closed flagship models and open-weight alternatives, making it useful for cost planning as well as capability research.

The project is open source and free to use, and it is intended to be consumed programmatically. Developers can pull the catalogue into their own tooling through a JSON API or a type-safe SDK, which makes it a practical backend for dashboards, routing logic, or internal cost calculators rather than just a reference page to browse.

**Pricing & Plans:** Models.dev is free and open source. It is a reference database, so the prices it lists are the per-million-token rates charged by the model providers themselves, not a fee for using the site.

- **Canonical model identifiers:** Every model uses a consistent provider/model format so the same model across providers can be compared directly.
- **Specification comparison:** Side-by-side context window, output limit, reasoning, tool calling, structured output, and temperature support.
- **Pricing transparency:** Input and output prices per million tokens listed alongside release and update dates.
- **Open and closed models:** Covers closed flagship APIs and open-weight models from many labs in one sortable catalogue.
- **Developer access:** Consume the catalogue through a JSON API or a type-safe SDK for your own tools and dashboards.

**Strengths:** Free and open source with no account required; Consistent canonical identifiers make cross-provider comparison reliable; Covers pricing, limits, and capabilities in one sortable table; Available as a JSON API and type-safe SDK for programmatic use

**Limitations:** It is a reference catalogue, not an inference or hosting service; Data quality depends on community and maintainer updates keeping pace with releases; Interface is aimed at developers and offers little guidance for non-technical users

[Profile (Markdown)](https://openaitools.app/tool/models-dev.md)

## Frequently Asked Questions

### How do Clay and Models.dev compare in monthly traffic?

Clay has 1,267,465 monthly visits, while Models.dev has 200,451. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Clay has a month-over-month growth rate of -2.7%; Models.dev has -3.9%.

### How does pricing compare?

Clay: Freemium, Free Trial, Contact for Pricing. Clay uses flexible, plan-based pricing with a 14-day free trial and a free entry point for individuals getting started, while larger teams and enterprises are quoted based on seats, credits, and data usage. Contact Clay for detailed enterprise pricing. Models.dev: Free. Models.dev is free and open source. It is a reference database, so the prices it lists are the per-million-token rates charged by the model providers themselves, not a fee for using the site.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Zapier](https://openaitools.app/tool/zapier-com) | 5,065,248 | +0.4% | Freemium, Free Trial, Paid | Automate work across thousands of apps — no code required | [.md](https://openaitools.app/tool/zapier-com.md) |
| 2 | [Instantly](https://openaitools.app/tool/instantly) | 2,336,279 | +6% | Paid, Contact for Pricing | Combines cold email campaigns with verified leads, but focuses more on outreach execution than deep enrichment. | [.md](https://openaitools.app/tool/instantly.md) |
| 3 | [Outreach](https://openaitools.app/tool/outreach) | 958,599 | +0.4% | Contact for Pricing | AI agents that work the revenue lifecycle alongside your sellers | [.md](https://openaitools.app/tool/outreach.md) |
| 4 | [Smartlead](https://openaitools.app/tool/smartlead-ai) | 952,377 | +4.3% | Free Trial, Paid | Excels at cold email deliverability and automation, but offers fewer options for complex multi-source data enrichment. | [.md](https://openaitools.app/tool/smartlead-ai.md) |
| 5 | [Success.ai](https://openaitools.app/tool/success-ai) | 547,073 | +6.3% | Freemium, Free Trial | Offers lead generation and email warmup features, but lacks the deep data orchestration and scraping flexibility. | [.md](https://openaitools.app/tool/success-ai.md) |
| 6 | [Gumloop](https://openaitools.app/tool/gumloop) | 379,557 | -21.1% | Freemium, Paid, Contact for Pricing | Build, share, and control AI agents that actually do the work | [.md](https://openaitools.app/tool/gumloop.md) |
| 7 | [Copy.ai](https://openaitools.app/tool/copy-ai) | 344,338 | -14.8% | Freemium, Paid | Provides unified sales prospecting workflows, but is less flexible for custom spreadsheet-based data enrichment. | [.md](https://openaitools.app/tool/copy-ai.md) |
| 8 | [Stork](https://openaitools.app/tool/stork) | 201,544 | +2.3% | Free | Includes model pricing trackers and developer news alongside tools directories, but less focused on raw API specs. | [.md](https://openaitools.app/tool/stork.md) |
| 9 | [Reply.io](https://openaitools.app/tool/reply-io) | 193,261 | -1.7% | Free Trial, Paid, Contact for Pricing | AI sales engagement and cold email outreach on autopilot | [.md](https://openaitools.app/tool/reply-io.md) |
| 10 | [Landbase](https://openaitools.app/tool/landbase) | 76,178 | +32.5% | Paid (usage-based credits) | Turns natural language prompts into verified contact audiences, but lacks the granular waterfall enrichment customization of Clay. | [.md](https://openaitools.app/tool/landbase.md) |

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Source: https://openaitools.app/compare/clay-2-0-vs-models-dev

More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)
